Deeplearning4j Tutorials

While Deeplearning4j is written in Java, the Java Virtual Machine (JVM) lets you import and share code in other JVM languages. These tutorials are written in Scala, the de facto standard for data science in the Java environment. There’s nothing stopping you from using any other interpreter such as Java, Kotlin, or Clojure.

If you’re coming from non-JVM languages like Python or R, you may want to read about how the JVM works before using these tutorials. Knowing the basic terms such as classpath, virtual machine, “strongly-typed” languages, and functional programming will help you debug, as well as expand on the knowledge you gain here. If you don’t know Scala and want to learn it, Coursera has a great course named Functional Programming Principles in Scala.

The tutorials are currently being reworked. You will likely find stumbling points. If you need any support while working through them, feel free to ask questions on https://community.konduit.ai/.

Tutorials covering basic DL4J features

pageQuickstart with MNISTpageMultiLayerNetwork And ComputationGraphpageLogistic RegressionpageBuilt-in Data IteratorspageFeed Forward NetworkspageBasic AutoencoderpageAdvanced AutoencoderpageConvolutional NetworkspageRecurrent NetworkspageEarly StoppingpageLayers and PreprocessorspageHyperparameter OptimizationpageUsing Multiple GPUs

End to End Tutorials showing specific solutions

pageClinical Time Series LSTMpageSea Temperature Convolutional LSTMpageSea Temperature Convolutional LSTM 2pageInstacart Multitask ExamplepageInstacart Single Task ExamplepageCloud Detection Example

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